Modified two-phase model with hybrid control for gas phase propylene copolymerization in fluidized bed reactors

Shamiri, Ahmad and Wong, S.W. and Zanil, M.F. and Hussain, Mohd Azlan and Mostoufi, N. (2015) Modified two-phase model with hybrid control for gas phase propylene copolymerization in fluidized bed reactors. Chemical Engineering Journal, 264. pp. 706-719. ISSN 1385-8947, DOI https://doi.org/10.1016/j.cej.2014.11.104.

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Abstract

In order to explore the dynamic behavior and process control of reactor temperature, a modified two-phase dynamic model for gas phase propylene copolymerization in a fluidized bed reactor is developed in which the entrainment of solid particles is considered. The modified model was compared with well-mixed and two-phase models in order to investigate the dynamic modeling response. The modified two-phase model shows close dynamic response to the well-mixed and two-phase models at the start of the polymerization, but begins to diverge with time. The proposed modified two-phase and two-phase models were validated with actual plant data. It was shown that the predicted steady state temperature by the modified two-phase model was closer to actual plant data compared to those obtained by the two-phase model. Advanced control system using a hybrid controller (a simple designed Takagi-Sugeno fuzzy logic controller (FLC)) integrated with the adaptive neuro-fuzzy inference system (ANFIS) controller was implemented to control the reactor temperature and compared with the FLC and conventional PID controller. The results show that the hybrid controller (ANFIS and FLC controller) performed better in terms of set point tracking and disturbance rejection compared to the FLC and conventional PID controllers. (C) 2014 Elsevier B.V. All rights reserved.

Item Type:	Article
Funders:	Research Council of the University of Malaya UM.C/HIR/MOHE/ENG/25
Additional Information:	Cc2rh Times Cited:0 Cited References Count:39
Uncontrolled Keywords:	Olefin polymerization; Dynamic two-phase model; Entrainment; Adaptive neuro-fuzzy inference system; Fuzzy logic controller
Subjects:	T Technology > T Technology (General) T Technology > TP Chemical technology
Divisions:	Faculty of Engineering
Depositing User:	Mr Jenal S
Date Deposited:	02 Sep 2015 04:15
Last Modified:	10 Feb 2021 03:56
URI:	http://eprints.um.edu.my/id/eprint/14020

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